Can a Swarm of (A2A) Agents do Cybersecurity?
Last Updated on August 29, 2025 by Editorial Team
Author(s): Michael Chen
Originally published on Towards AI.
Oh wow… It’s been a while since my last article. Time to get disciplined with writing!😉
I’ve wanted to write about LLMs/AI, exploring not just the tech but also potential societal impacts. During a recent hackathon, I experimented with AgenticLLMs, leveraging Anthropic’s MCP and Google’s A2A protocol. I’ll save the societal and philosophical musings for the end — feel free to skip them if they’re not your thing. 😉

This article discusses the development of a swarm of AgenticLLM agents aimed at assisting SOC analysts by providing actionable insights based on SIEM alerts. It delves into the architecture, components, and interactions of these agents during a hackathon, emphasizing the practicality of utilizing Google’s A2A protocol and Anthropic’s MCP. The author reflects on the broader implications of AI and LLM technologies, drawing parallels between human learning and machine learning capabilities, while also addressing potential concerns regarding reliance on these technologies and the future of software engineering roles in an AI-centric world.
Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.